First trimester, one-tube screening for pregnancy complications via placental biomarkers
- 1International Peace Maternity and Child Health Hospital of China Welfare Institution (IPMCH), 910 Heng Shan Road, Shanghai, 200030 China
- 2School of Medicine, Shanghai Jiao Tong University, Shanghai Key Laboratory of Embryo Original Diseases, Shanghai, China
- 3Revvity, Ltd., Women and Children Diagnosis, Shanghai, China
Abstract
Background: Early pregnancy screening to identify high-risk women for targeted prevention is effective for reducing pregnancy complications. Placental biomarkers, including PlGF and PAPP-A, are linked to adverse outcomes, yet their combined predictive value for pregnancy complications remains unclear. Here, a retrospective cohort study was conducted to assess first-trimester prediction models incorporating PlGF, PAPP-A, and maternal factors for major obstetric complications.
Methods: This was a retrospective cohort study using data that were prospectively collected during first-trimester screening. A cohort study was conducted at the International Peace Maternity and Child Health Hospital of China Welfare Institution (Shanghai, China) from December 2021 to October 2022. A total of 4046 participants were recruited during the first-trimester screening, excluding those with miscarriages and those without delivery data. In our routine screening, all pregnant women were tested for placental growth factor (PlGF) and pregnancy-associated plasma protein A (PAPP-A). The mean arterial pressure (MAP) and uterine artery pulsatility index (UTPI) were also measured in accordance with the Fetal Medicine Foundation guidelines, along with maternal characteristics and medical history collected via face-to-face interviews. Multivariable logistic regression was used for model development. Model performance was evaluated by the area under the receiver operating characteristic curve (AUC).
Results: Among 4046 initially recruited participants, data from 3910 participants regarding fetal growth restriction (FGR), gestational diabetes mellitus (GDM), placenta previa and preterm birth (PTB) were analyzed. For the PE analysis, a subgroup of 1,588 women with available UTPI measurements was evaluated. The best models for predicting FGR were the indicator height, PAPP-A levels, and PlGF levels, with an AUC of 0.742 (95% CI: 0.633–0.851). Regarding GDM prediction, the model including BMI and PAPP-A levels had the best AUC (0.667, 95% CI: 0.622–0.713). With respect to placenta previa prediction, the model including age and PlGF levels had the best AUC (0.765, 95% CI: 0.588–0.941). For PTB, indicators such as the PlGF multiples of the median (MoM), PAPP-A, type I diabetes and systemic lupus erythematosus had the best performance, with an AUC of 0.665 (95% CI: 0.553–0.776). For PE screening using the Fetal Medicine Foundation (FMF) competing-risk model (PAPP-A, PIGF, MAP, and UTPI), the model achieved an AUC of 0.847 for preterm PE (< 37 weeks), with a detection rate of 50.00%, and an AUC of 0.777 for term PE (≥ 37 weeks), with a detection rate of 95.12% at the recommended risk cutoff of 1 in 100.
Conclusion: First-trimester screening using PlGF, PAPP-A, and maternal factors shows preliminary associations with common obstetric complications, suggesting the potential utility of these biomarkers in early risk stratification, providing a proof-of-concept tool for early risk stratification and improved management of high-risk pregnancies to reduce maternal and fetal morbidity. However, these models require validation in larger, more diverse populations before clinical consideration.
Supplementary Information: The online version contains supplementary material available at https://doi.org/10.1186/s12884-026-09417-2.
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BibTeX
@article{hua2026first,
title = {{First trimester, one-tube screening for pregnancy complications via placental biomarkers}},
author = {Renyi Hua and Shuyuan Li and Xu Han and Ziyuan Tang and Baoying Ye and Yuru Tan and Shan Wang and Jinling Sun and Weiwei Cheng and Yanlin Wang},
journal = {BMC Pregnancy and Childbirth},
year = {2026},
month = jun,
doi = {10.1186/s12884-026-09417-2},
url = {https://doi.org/10.1186/s12884-026-09417-2},
note = {CC BY-NC-ND 4.0},
}
RIS
TY - JOUR
TI - First trimester, one-tube screening for pregnancy complications via placental biomarkers
AU - Renyi Hua
AU - Shuyuan Li
AU - Xu Han
AU - Ziyuan Tang
AU - Baoying Ye
AU - Yuru Tan
AU - Shan Wang
AU - Jinling Sun
AU - Weiwei Cheng
AU - Yanlin Wang
PY - 2026
DA - 2026/06/15
JO - BMC Pregnancy and Childbirth
DO - 10.1186/s12884-026-09417-2
UR - https://doi.org/10.1186/s12884-026-09417-2
AB - Background: Early pregnancy screening to identify high-risk women for targeted prevention is effective for reducing pregnancy complications. Placental biomarkers, including PlGF and PAPP-A, are linked to adverse outcomes, yet their combined predictive value for pregnancy complications remains unclear. Here, a retrospective cohort study was conducted to assess first-trimester prediction models incorporating PlGF, PAPP-A, and maternal factors for major obstetric complications. Methods: This was a retrospective cohort study using data that were prospectively collected during first-trimester screening. A cohort study was conducted at the International Peace Maternity and Child Health Hospital of China Welfare Institution (Shanghai, China) from December 2021 to October 2022. A total of 4046 participants were recruited during the first-trimester screening, excluding those with miscarriages and those without delivery data. In our routine screening, all pregnant women were tested for placental growth factor (PlGF) and pregnancy-associated plasma protein A (PAPP-A). The mean arterial pressure (MAP) and uterine artery pulsatility index (UTPI) were also measured in accordance with the Fetal Medicine Foundation guidelines, along with maternal characteristics and medical history collected via face-to-face interviews. Multivariable logistic regression was used for model development. Model performance was evaluated by the area under the receiver operating characteristic curve (AUC). Results: Among 4046 initially recruited participants, data from 3910 participants regarding fetal growth restriction (FGR), gestational diabetes mellitus (GDM), placenta previa and preterm birth (PTB) were analyzed. For the PE analysis, a subgroup of 1,588 women with available UTPI measurements was evaluated. The best models for predicting FGR were the indicator height, PAPP-A levels, and PlGF levels, with an AUC of 0.742 (95% CI: 0.633–0.851). Regarding GDM prediction, the model including BMI and PAPP-A levels had the best AUC (0.667, 95% CI: 0.622–0.713). With respect to placenta previa prediction, the model including age and PlGF levels had the best AUC (0.765, 95% CI: 0.588–0.941). For PTB, indicators such as the PlGF multiples of the median (MoM), PAPP-A, type I diabetes and systemic lupus erythematosus had the best performance, with an AUC of 0.665 (95% CI: 0.553–0.776). For PE screening using the Fetal Medicine Foundation (FMF) competing-risk model (PAPP-A, PIGF, MAP, and UTPI), the model achieved an AUC of 0.847 for preterm PE (< 37 weeks), with a detection rate of 50.00%, and an AUC of 0.777 for term PE (≥ 37 weeks), with a detection rate of 95.12% at the recommended risk cutoff of 1 in 100. Conclusion: First-trimester screening using PlGF, PAPP-A, and maternal factors shows preliminary associations with common obstetric complications, suggesting the potential utility of these biomarkers in early risk stratification, providing a proof-of-concept tool for early risk stratification and improved management of high-risk pregnancies to reduce maternal and fetal morbidity. However, these models require validation in larger, more diverse populations before clinical consideration. Supplementary Information: The online version contains supplementary material available at https://doi.org/10.1186/s12884-026-09417-2.
SN - 1471-2393
ER -